Explore the world of Micro Graph Transformers and their impact on small language models in this insightful podcast episode featuring Jon Cooke, CTO of Dataception. Dive into the challenges of productionizing large language models, including cost optimization, latency requirements, and output reliability. Learn about specialist deconstructed Encoder/Decoder Transformers and their role in accelerating data product ecosystems. Discover how data virtualization, intelligent agents, and iterative development contribute to building efficient, business-facing analytics solutions. Gain valuable insights from Cooke's 20-year experience in data, analytics, and AI as he discusses the evolution of data roles, the integration of data and machine learning, and strategies for achieving product-market fit in the rapidly evolving field of AI and data products.
Micro Graph Transformer - Powering Small Language Models for Data Product Ecosystems
Overview
Syllabus
[] AI in Production Conference teaser
[] Jon's preferred coffee
[] Takeaways
[] Please like, share, and subscribe to our MLOps channels!
[] Backpacking, traveling, and almost cast for Lord of the Rings
[] Jon's tech background
[] Dataception
[] Data Challenges: Delays & Causes
[] Data Virtualization for Agility
[] Large Company Change Challenges
[] Sales Tools Migration Challenges
[] Data and ML Integration
[] Data Roles Evolution
[] Tech for Prototyping Acceleration
[] LLM Enables Natural Language Data Analytics
[] Ensuring Reliable AI Information
[] Proxy Routing and Intelligent Agents
[] Human API for Data
[] Engineer Success with Growth
[] Tech CEO Balancing Act
[] Iterative Development for Product-Market Fit
[] Wrap up
Taught by
MLOps.community
